Artwork

内容由Hasan Akram提供。所有播客内容(包括剧集、图形和播客描述)均由 Hasan Akram 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
Player FM -播客应用
使用Player FM应用程序离线!

Autonomous Vehicle Data Annotation

47:53
 
分享
 

Manage episode 294631449 series 2486140
内容由Hasan Akram提供。所有播客内容(包括剧集、图形和播客描述)均由 Hasan Akram 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

FREE WEBINAR - ISO/SAE 21434 - AUTOMOTIVE CYBERSECURITY

https://www.lordsofcarhackers.com/webinar

Annotating the data in the correct way is very important for the autonomous vehicle industry. It is the process of tagging or classifying the objects in the frame as captured by the autonomous vehicle.

In this episode, Philip Kessler will talk about Understand.ai and how their company annotates data. Among other interesting topics, he will also answer questions such as:

What are the problems being addressed by Understand.ai?

How big is the annotation industry today?

How often do we have to do data annotation?

When it comes to AI, why do we need global data?

How does Understand.ai annotate complex data?

What are the different types of annotation?

What is Understand.ai’s primary business model?

How does Understand.ai validate the correctness of their annotation?

How is data security handled?

What are the main business and technological challenges of Understand.ai?

By the end of this insightful discussion, you will have an idea of how data annotation works in autonomous driving and how Understand.ai performs this task.

#artificialintelligence #machinelearning #dataannotation #annotations #AutomotiveIndustry #autonomousvehicles #autonomousvehicle #Ai #artificialintelligenceai #artificialintelliegence

  continue reading

77集单集

Artwork
icon分享
 
Manage episode 294631449 series 2486140
内容由Hasan Akram提供。所有播客内容(包括剧集、图形和播客描述)均由 Hasan Akram 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

FREE WEBINAR - ISO/SAE 21434 - AUTOMOTIVE CYBERSECURITY

https://www.lordsofcarhackers.com/webinar

Annotating the data in the correct way is very important for the autonomous vehicle industry. It is the process of tagging or classifying the objects in the frame as captured by the autonomous vehicle.

In this episode, Philip Kessler will talk about Understand.ai and how their company annotates data. Among other interesting topics, he will also answer questions such as:

What are the problems being addressed by Understand.ai?

How big is the annotation industry today?

How often do we have to do data annotation?

When it comes to AI, why do we need global data?

How does Understand.ai annotate complex data?

What are the different types of annotation?

What is Understand.ai’s primary business model?

How does Understand.ai validate the correctness of their annotation?

How is data security handled?

What are the main business and technological challenges of Understand.ai?

By the end of this insightful discussion, you will have an idea of how data annotation works in autonomous driving and how Understand.ai performs this task.

#artificialintelligence #machinelearning #dataannotation #annotations #AutomotiveIndustry #autonomousvehicles #autonomousvehicle #Ai #artificialintelligenceai #artificialintelliegence

  continue reading

77集单集

Усі епізоди

×
 
Loading …

欢迎使用Player FM

Player FM正在网上搜索高质量的播客,以便您现在享受。它是最好的播客应用程序,适用于安卓、iPhone和网络。注册以跨设备同步订阅。

 

快速参考指南